Papers by Roman Teucher
Fact Finder - Enhancing Domain Expertise of Large Language Models by Incorporating Knowledge Graphs (2026.eacl-demo)
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Daniel Steinigen, Roman Teucher, Timm Heine Ruland, Max Rudat, Nicolas Flores-Herr, Peter Fischer, Nikola Milosevic, Christopher Schymura, Angelo Ziletti
| Challenge: | Recent advances in Large Language Models have demonstrated their proficiency in answering natural language queries. |
| Approach: | They propose a system that augments Large Language Models with domain-specific knowledge graphs . they evaluate a medical KG and use a KG-based retrieval approach to enhance factual correctness . |
| Outcome: | The proposed system surpasses a standalone LLM in accuracy and completeness on a medical KG dataset. |
CarExpert: Leveraging Large Language Models for In-Car Conversational Question Answering (2023.emnlp-industry)
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Md Rashad Al Hasan Rony, Christian Suess, Sinchana Ramakanth Bhat, Viju Sudhi, Julia Schneider, Maximilian Vogel, Roman Teucher, Ken Friedl, Soumya Sahoo
| Challenge: | Large language models (LLMs) have demonstrated remarkable performance by following natural language instructions without fine-tuning them on domain-specific tasks and data. |
| Approach: | They propose an in-car retrieval-augmented conversational question-answering system that uses large language models to generate natural, safe and domain-specific answers. |
| Outcome: | The proposed system outperforms state-of-the-art LLMs in generating safe and domain-specific answers. |